Clary Jacob M, Holder Aaron M, Musgrave Charles B
Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States.
Materials and Chemical Science and Technology Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States.
ACS Appl Mater Interfaces. 2020 Oct 28;12(43):48553-48564. doi: 10.1021/acsami.0c13298. Epub 2020 Oct 19.
The design of multinary solid-state material systems that undergo reversible phase changes via changes in temperature and pressure provides a potential means of safely storing hydrogen. However, fully mapping the stabilities of known or newly targeted compounds relative to competing phases at reaction conditions has previously required many stringent experiments or computationally demanding calculations of each compound's change in Gibbs energy with respect to temperature, (). In this work, we have extended the approach of constructing chemical potential phase diagrams based on Δ() to enable the analysis of phase stability at non-zero temperatures. We first performed density functional theory calculations to compute the formation enthalpies of binary, ternary, and quaternary compounds within several compositional spaces of current interest for solid-state hydrogen storage. Temperature effects on solid compound stability were then accounted for using our recently introduced machine learned descriptor for the temperature-dependent contribution () to the Gibbs energy (). From these Gibbs energies, we evaluated each compound's stability relative to competing compounds over a wide range of conditions and show using chemical potential and composition phase diagrams that the predicted stable phases and H release reactions are consistent with experimental observations. This demonstrates that our approach rapidly computes the thermochemistry of hydrogen release reactions for compounds at sufficiently high accuracy relative to experiment to provide a powerful framework for analyzing hydrogen storage materials. This framework based on () enables the accelerated discovery of active materials for a variety of technologies that rely on solid-state reactions involving these materials.
通过温度和压力变化经历可逆相变的多元固态材料系统的设计，为安全储存氢气提供了一种潜在手段。然而，以前要全面绘制已知或新目标化合物相对于反应条件下竞争相的稳定性，需要对每种化合物的吉布斯自由能随温度的变化进行许多严格的实验或计算量很大的计算。在这项工作中，我们扩展了基于Δ()构建化学势相图的方法，以能够分析非零温度下的相稳定性。我们首先进行密度泛函理论计算，以计算当前固态储氢感兴趣的几个成分空间内二元、三元和四元化合物的生成焓。然后，使用我们最近引入的机器学习描述符来考虑温度对固态化合物稳定性的影响，该描述符用于描述吉布斯自由能()的温度依赖性贡献()。根据这些吉布斯自由能，我们评估了每种化合物在广泛条件下相对于竞争化合物的稳定性，并使用化学势和组成相图表明，预测的稳定相和氢释放反应与实验观察结果一致。这表明，我们的方法相对于实验能够以足够高的精度快速计算化合物氢释放反应的热化学，从而为分析储氢材料提供了一个强大的框架。这个基于()的框架能够加速发现用于各种依赖涉及这些材料的固态反应的技术的活性材料。
